Quantitative Analytics & Model Analyst Senior - Data Operations and Machine Learning Operations
Core
Design, engineer, deploy, and support scalable AI and machine learning solutions, transitioning analytical and ML solutions from development into production environments.
Role type
Senior MLOps Engineer (AI/ML Operations)
Builds
Scalable frameworks, reusable components, and production-ready AI/ML models and agentic solutions
Domain
Financial Services / Machine Learning Operations
Deliverable
production ML models
Required skills
Python, PySpark, SQL, Docker, Git, CI/CD, AWS, Azure, OpenShift Container Platform, model lifecycle management, infrastructure-as-code
Preferred skills
Banking/financial services experience, model governance, data engineering
Technologies
Python, PySpark, SQL, Docker, Git, Jenkins, JIRA, Confluence, OpenShift, AWS, Azure
Responsibilities
Build scalable frameworks for model development and deployment; Collaborate with data scientists to operate ML solutions in production; Manage model releases, version control, and deployment processes; Establish infrastructure standards for model deployment; Troubleshoot operational issues across AI/ML ecosystems
Seniority
Senior, hands-on IC